1. Field of the Invention
The present invention relates to signal processing and classification and more particularly to a technique for determining the likelihood that a received signal is the result of a preselected event. The invention further relates to a method for classifying signals utilizing a range of selective criteria which is applied in such a manner to received data so as to form an array of likelihood values from which a best fit is selected.
2. Related Technical Art
Previous attempts to classify and analyze signals or data as related to specific events have generally been limited to applying classical "crisp" of fixed logical relationships to extracted signal features of parameters. A signal is typically classified through application of, and strict adherence to, a limited set of predefined signal parameters to which a highly constrained set of probabilities is applied to decide to what specific event or class of events a signal relates. That is, the received data is employed in a technique that requires the signal parameters to fit exactly one set of values. When a sufficiently large database of background classification information exists and processing time is not limited, this process works well.
Unfortunately the feature or parameter set describing a signal or observed object cannot always be crisply defined because of incomplete or inaccurate knowledge about the events being observed. This is especially true where speed is often of the essence in gathering data, under less than ideal conditions with a minimum of computing resources and accuracy of data. This is especially true where the rules for structuring the accrued database are less than precise. The available information in a knowledge database is often only sufficient to place a given parameter value under analysis in a general category. Therefore, it would be desirable to apply some form of "fuzzy" or less rigid logical classification structure to the process.
What is needed is a method and apparatus for applying flexible classification rules or approximate likelihoods to arrive at a decision in a highly efficient structure which is easily constructed using currently available technology.
Although the field of "fuzzy logic" was established by the mathematical community in the 1920's, it was not until about 1960 that the engineering community became aware of it, and not until in the late 1980's before the Japanese began applying the methodology to control of trains, elevators, heating plants, and a variety of consumer products (e.g. autofocus cameras).
In addition, while there is at least one company in the United States specializing in fuzzy logic engineering (Togi InfraLogic) and several textbooks currently available on the subject, see: G. J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty, and Information, Prentice Hall, 1988; J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, 1987; and B. Kosko, Neutral Networks and Fuzzy Systems, Prentice Hall, 1992; there appears to be remarkably few applications, particularly within the United States.